Interferometry delivers the highest angular resolution. It is being used extensively
in radio astronomy and, since about a decade, it is becoming an important player in
infrared astronomy. However, infrared interferometry is restricted to sparse arrays
and no full-phase information is recovered. While imaging is arguably the most intuitive
way to analyze interferometric data, recovering images from sparsely sampled visibilities
is an "ill-posed" problem. The current algorithms work under the framework of using
regularized minimization techniques. These algorithms strongly depend on the priors
and hyperparameters pre-defined. This gives rise to ambiguities and artifacts in the
interpretation of the images and limits their accuracy/precision as well as their
signal-to-noise ratio if the priors/regularizers are not well-defined. Also, it means
that imaging is the domain of a handful of highly experienced astronomers, thus keeping
the interferometric community small. CASSINI-AUTOMAP aims at disrupting this situation
by creating a novel framework for interferometric image reconstruction. This project
is based on the exploitation of the compressibility of a signal (following the principles
of theory of Compressed Sensing) with a novel optimization scheme supported by Neural
Networks. In particular, we focus our efforts in designing a Neural Network with adaptive
activation functions to find an optimal mapping system between the infrared interferometric
data and the reconstructed images. The online adaptability of the Neural Network frees
us from having to rely on strong priors, making the reconstructions more accurate
and less dependent on users' inputs. Our preliminar network architecture has been
tested with Sparse Aperture Masking (SAM) data taken with the infrared camera NACO
at the Very Large Telescope and it demonstrates the potential and reliability of the
algorithm by recovering the interferometric observables. Future improvements on the
software aims at analyzing data from instruments like GRAVITY at the Very Large Telescope
Interferometer or the Sparse Aperture Masking mode of the James Webb Space Telescope.
